Wenbo Gong

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 21

Top Topics

Conditional Independence

Causal Discovery

Markov Chain Monte Carlo

Structure Learning

Top Venues

Publications

Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR (2024)
Benjie Wang, Joel Jennings, Wenbo Gong
Neural structure learning with stochastic differential equations. ICLR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS (2023)
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. CoRR (2023)
Benjie Wang, Joel Jennings, Wenbo Gong
Neural Structure Learning with Stochastic Differential Equations. CoRR (2023)
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. ICLR (2023)
Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan
Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR (2023)
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Simultaneous Missing Value Imputation and Structure Learning with Groups. NeurIPS (2022)
Wenbo Gong, Digory Smith, Zichao Wang, Craig Barton, Simon Woodhead, Nick Pawlowski, Joel Jennings, Cheng Zhang
Instructions and Guide: Causal Insights for Learning Paths in Education. CoRR (2022)
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise. CoRR (2022)
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. CoRR (2022)
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato
Sliced Kernelized Stein Discrepancy. ICLR (2021)
Wenbo Gong, Yingzhen Li
Interpreting diffusion score matching using normalizing flow. CoRR (2021)
Wenbo Gong, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato
Active Slices for Sliced Stein Discrepancy. CoRR (2021)
Wenbo Gong, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato
Active Slices for Sliced Stein Discrepancy. ICML (2021)
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato
Sliced Kernelized Stein Discrepancy. CoRR (2020)
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato
Meta-Learning For Stochastic Gradient MCMC. ICLR (Poster) (2019)
Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. CoRR (2019)
Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. NeurIPS (2019)
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato
Meta-Learning for Stochastic Gradient MCMC. CoRR (2018)